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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Link functions\n",
      "\n",
      "[Tom Wallis](http://www.tomwallis.info) and [Philipp Berens](http://philippberens.wordpress.com/)\n",
      "\n",
      "The University of T\u00fcbingen"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import scipy as sp\n",
      "import pandas as pd\n",
      "import patsy\n",
      "import seaborn as sns\n",
      "import statsmodels.formula.api as smf\n",
      "import statsmodels.api as sm\n",
      "import matplotlib.pyplot as plt\n",
      "import itertools\n",
      "\n",
      "%matplotlib inline\n",
      "\n",
      "sns.set_style(\"white\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Link functions\n",
      "\n",
      "Recall from last week's lecture that the general form of the GLM is \n",
      "\n",
      "$y = f(\\mathbf{X} \\beta) + \\epsilon$\n",
      "\n",
      "All the models we've considered up until now are *linear* models: the *link function* $f()$ is the identity --- that is, it doesn't change $\\mathbf{X} \\beta$ at all, and the noise $\\epsilon$ is assumed to be Gaussian.\n",
      "\n",
      "But for many response variables, linear predictions don't make a lot of sense. Consider one of the example datasets we've given you: \"g-forces\" (from [here](http://www.statsci.org/data/general/gforces.html)). From the description:\n",
      "\n",
      "*Military pilots sometimes black out when their brains are deprived of oxygen due to G-forces during violent maneuvers.* \n",
      "\n",
      "<img src=\"pics_for_lectures/topgun.jpg\">\n",
      "\n",
      "*Glaister and Miller (1990) produced similar symptoms by exposing volunteers\u2019 lower bodies to negative air pressure, likewise decreasing oxygen to the brain. The data lists the subjects' ages and whether they showed syncopal blackout related signs (pallor, sweating, slow heartbeat, unconsciousness) during an 18 minute period.*\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "So Glaister and Miller (1990) wanted to know whether the propensity to black out was related to the subject's age. They tested this in 8 people. Let's import the data:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gf = pd.read_csv('../Datasets/gforces.txt', sep='\\t')\n",
      "# make all columns lower case:\n",
      "gf.columns = [c.lower() for c in gf.columns]\n",
      "print(gf)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  subject  age  signs\n",
        "0      JW   39      0\n",
        "1      JM   42      1\n",
        "2      DT   20      0\n",
        "3      LK   37      1\n",
        "4      JK   20      1\n",
        "5      MK   21      0\n",
        "6      FP   41      1\n",
        "7      DG   52      1\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Note that the response variable we're trying to predict (`signs`) takes on *only* one of two possible values: either the subject showed blackout signs (y = 1) or did not (y = 0). \n",
      "\n",
      "*Aside: the numerical values 0 and 1 are used by convention and for mathematical convenience. Think of it like \"the presence of somthing (1) and the absence of something (0)\"*.\n",
      "\n",
      "What happens if we fit an ordinary (Gaussian error) linear regression to these data?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fit_lm = smf.glm('signs ~ age', gf).fit()\n",
      "print(fit_lm.summary())\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                 Generalized Linear Model Regression Results                  \n",
        "==============================================================================\n",
        "Dep. Variable:                  signs   No. Observations:                    8\n",
        "Model:                            GLM   Df Residuals:                        6\n",
        "Model Family:                Gaussian   Df Model:                            1\n",
        "Link Function:               identity   Scale:                  0.234334625323\n",
        "Method:                          IRLS   Log-Likelihood:                -4.3968\n",
        "Date:                Tue, 24 Feb 2015   Deviance:                       1.4060\n",
        "Time:                        20:39:09   Pearson chi2:                     1.41\n",
        "No. Iterations:                     4                                         \n",
        "==============================================================================\n",
        "                 coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
        "------------------------------------------------------------------------------\n",
        "Intercept     -0.0998      0.540     -0.185      0.853        -1.159     0.959\n",
        "age            0.0213      0.015      1.415      0.157        -0.008     0.051\n",
        "==============================================================================\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Let's have a look at the model predictions\n",
      "sns.regplot('age', 'signs', gf)\n",
      "sns.despine(offset=10);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
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        }
       },
       "output_type": "display_data",
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AeySKnVYrVa1v1RT4vkL6J8COCCoAAABdFkWxrlWq2txuKPA95UM+ggF3w98SAACALmlG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\nTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10bee0ef0>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notice how the data are only `0s` or `1s`, but that our model can happily predict values outside this range. Moreover, our model expects the errors to be Gaussian, and they clearly won't be. Therefore, this linear model is not appropriate for these data.\n",
      "\n",
      "What we want instead is to change the link function $f()$ from the identity (i.e. our prediction is just $\\mathbf{X} \\beta$ with Gaussian errors) to something more appropriate for the data we have. We are going to *transform* the linear predictor into a more appropriate range, by changing the link function.\n",
      "\n",
      "Our linear predictor can theoretically range from `-inf` to `+inf`. We want something that maps this range into the range 0--1. There are a number of options, but the most common is the [logistic function](http://mathworld.wolfram.com/SigmoidFunction.html):\n",
      "\n",
      "$y = \\frac{1}{1 + e^{-x}}$\n",
      "\n",
      "Let's plot what this does:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def logit(x): \n",
      "    return(1. / (1. + np.exp(-x)))\n",
      "\n",
      "x = np.linspace(-5, 5)  # imagine this is the linear predictor (inner product of X and beta)\n",
      "y = logit(x)\n",
      "plt.plot(x, y)\n",
      "sns.despine(offset=10)\n",
      "plt.vlines(0, 0, 1, linestyles='--')\n",
      "plt.hlines(0.5, -5, 5, linestyles='--')\n",
      "plt.yticks([0, 0.5, 1])\n",
      "plt.xlabel('Linear predictor value')\n",
      "plt.ylabel('Transformed value');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 283,
         "width": 396
        }
       },
       "output_type": "display_data",
       "png": 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bIcNKmmyMSTip76yT7suSlOrSmAAAeObpt7coEKg/X/bW2aOUkMDBewAguRcy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\nJKmo/h/7B8X3WseT4QAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10bf8bef0>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notice that as the linear predictor approaches negative infinity, its transformed value approaches zero -- but never goes below. Similarly, as the linear predictor approaches positive infinity, its value approaches one, but never above:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "logit(-np.inf)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "0.0"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "logit(np.inf)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "1.0"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The `logit` transform allows us to map our linear predictor into a bounded range. Note also that when the linear predictor is zero, the logit is 0.5. \n",
      "\n",
      "How can we now use this transformed value to predict dichotomous responses?"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Binomial distribution\n",
      "\n",
      "Since the response variable is dichotomous (either \"shows signs\" or \"does not show signs\"), an appropriate probability distribution to describe the data is the [*binomial distribution*](http://www.wolframalpha.com/input/?i=binomial+distribution). Just as the Normal distribution returns a probability density over a continuous dimension given a mean and standard deviation, the binomial distribution gives a probability mass over a discrete dimension (number of \"successes\"), given a number of \"trials\" and a probability of success, $p$ (note since $p$ is a probability, it can have any value from 0 to 1). \n",
      "\n",
      "The most common example used to demonstrate the binomial distribution is coin flipping. Imagine we have a fair coin ($p = 0.5$) and we flip it 50 times. How many heads (\"successes\") would we expect? The binomial distribution can tell us."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# code hacked from here: http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.stats.binom.html\n",
      "n, p = 50, 0.5\n",
      "fig, ax = plt.subplots(1, 1)\n",
      "x = np.arange(sp.stats.distributions.binom.ppf(0.001, n, p), \n",
      "              sp.stats.distributions.binom.ppf(0.999, n, p))\n",
      "ax.plot(x, sp.stats.distributions.binom.pmf(x, n, p), 'bo', ms=8, label='binom pmf')\n",
      "ax.vlines(x, 0, sp.stats.distributions.binom.pmf(x, n, p), colors='b', lw=5, alpha=0.5)\n",
      "sns.despine(offset=10);\n",
      "plt.xlabel('Number of successes')\n",
      "plt.xlim(0, 50)\n",
      "plt.ylabel('Probability mass');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
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zr6pq2CzOLbdTw8EWYDNwNjBTSHkNcCvwwYkdmXl3RFxC8b5ezIEen/OAOyfV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\nJEmS1FX+DznRT3iKriJAAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10bfbadd8>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now imagine we have a trick coin, which comes up heads 90% of the time. How many heads do we expect now?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "n, p = 50, 0.9\n",
      "fig, ax = plt.subplots(1, 1)\n",
      "x = np.arange(sp.stats.distributions.binom.ppf(0.001, n, p), \n",
      "              sp.stats.distributions.binom.ppf(0.999, n, p))\n",
      "ax.plot(x, sp.stats.distributions.binom.pmf(x, n, p), 'bo', ms=8, label='binom pmf')\n",
      "ax.vlines(x, 0, sp.stats.distributions.binom.pmf(x, n, p), colors='b', lw=5, alpha=0.5)\n",
      "sns.despine(offset=10);\n",
      "plt.xlabel('Number of successes')\n",
      "plt.xlim(0, 50)\n",
      "plt.ylabel('Probability mass');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 283,
         "width": 405
        }
       },
       "output_type": "display_data",
       "png": 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oRMSFwCvID0LsL+7dSX444x+mlK4qsz9JkiRJvamU7Ykj4n4R8THgo+QHI54E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\n1nZcqJiZmZmZWdtxoWJmZmZmZm3n/wGw91Pcoa1TRwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10dd9f4e0>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "So you can see that changing $p$ changes the number of successes we expect from a given number of trials (equivalently, the chance of a success on any one trial).\n",
      "\n",
      "Now, by assuming that our response distribution is binomially distributed, we can estimate the expected probability of showing blackout signs as a function of age. To do this, we use the logit transformed linear predictor as our estimate of $p$ in the binomial distribution. \n",
      "\n",
      "We can use statsmodel's `glm` function to find the regression weights that maximise the likelihood of the observed data, assuming that the data come from a binomial distribution:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fit = smf.glm('signs ~ age', \n",
      "              data=gf, \n",
      "              family=sm.families.Binomial(link=sm.families.links.logit)).fit()\n",
      "# note we don't have to specify the logit link above, since it's the default for the binomial distribution.\n",
      "\n",
      "print(fit.summary())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                 Generalized Linear Model Regression Results                  \n",
        "==============================================================================\n",
        "Dep. Variable:                  signs   No. Observations:                    8\n",
        "Model:                            GLM   Df Residuals:                        6\n",
        "Model Family:                Binomial   Df Model:                            1\n",
        "Link Function:                  logit   Scale:                             1.0\n",
        "Method:                          IRLS   Log-Likelihood:                -4.2173\n",
        "Date:                Tue, 24 Feb 2015   Deviance:                       8.4345\n",
        "Time:                        20:39:10   Pearson chi2:                     7.42\n",
        "No. Iterations:                     6                                         \n",
        "==============================================================================\n",
        "                 coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
        "------------------------------------------------------------------------------\n",
        "Intercept     -2.9209      2.647     -1.104      0.270        -8.108     2.266\n",
        "age            0.1057      0.080      1.315      0.188        -0.052     0.263\n",
        "==============================================================================\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We get a summary table with regression coefficients as before. Note that a few things have changed: in particular, see that the `Model Family` is now \"Binomial\", and the `Link Function` is the logit. This is also called a **logistic regression**, because it uses the logit link function.\n",
      "\n",
      "How do the regression coefficients above compare to the linear, Gaussian model we fit before?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(fit_lm.summary())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                 Generalized Linear Model Regression Results                  \n",
        "==============================================================================\n",
        "Dep. Variable:                  signs   No. Observations:                    8\n",
        "Model:                            GLM   Df Residuals:                        6\n",
        "Model Family:                Gaussian   Df Model:                            1\n",
        "Link Function:               identity   Scale:                  0.234334625323\n",
        "Method:                          IRLS   Log-Likelihood:                -4.3968\n",
        "Date:                Tue, 24 Feb 2015   Deviance:                       1.4060\n",
        "Time:                        20:39:10   Pearson chi2:                     1.41\n",
        "No. Iterations:                     4                                         \n",
        "==============================================================================\n",
        "                 coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
        "------------------------------------------------------------------------------\n",
        "Intercept     -0.0998      0.540     -0.185      0.853        -1.159     0.959\n",
        "age            0.0213      0.015      1.415      0.157        -0.008     0.051\n",
        "==============================================================================\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can see the regression coefficients are totally different numbers. However, our *design matrix* $\\mathbf{X}$ didn't change: it's still a column of ones and a column of `age`. The reason the coefficients are different is because in the logistic regression, the beta weights pass through the link function to give a prediction for the response variable. \n",
      "\n",
      "Let's run through what the regression coefficients mean in the logistic regression (`fit`).\n",
      "\n",
      "The `Intercept` is the value of the *linear predictor* (note: not the response!) when age = 0. In this case, we can't observe an age of zero, so the intercept is not very meaningful \n",
      "\n",
      "*Aside: To make the intercept more interpretable, we could centre the `age` variable by subtracting its mean -- this would make the intercept equal the linear predictor value when age is at its mean in the data. We could do this within the Patsy formula by writing `signs ~ center(age)`. We will avoid doing this here for simplicity.*\n",
      "\n",
      "The `age` coefficient tells us the change in the *linear predictor* for an increase in age of one year.\n",
      "\n",
      "To work out what these mean for the *response* value, we need to pass them through the logit function. As an example, let's consider the prediction for the chance a 28 year old person would show blackout signs."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "age = 28\n",
      "linear_predictor = fit.params[0] + fit.params[1]*age\n",
      "linear_predictor"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "0.038508192779235006"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pred = logit(linear_predictor)\n",
      "pred"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "0.50962585872402622"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "So our prediction for a 28 year old is that they would have about a 51% chance to black out. We can also compute this using the `predict` method of the fit object. Let's do that for a 65 year old:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fit.predict(exog={'age':65})"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "array([ 0.9810925])"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Our model predicts that a 65 year old would have a 98.1% chance of blacking out. What would happen if we tried making similar predictions from the (inappropriate) linear model?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fit_lm.predict(exog={'age': 65})"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "array([ 1.28585271])"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The linear model predicts a value of 1.28 for a 65 year old -- which makes no sense."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Plotting model predictions\n",
      "\n",
      "Let's plot our model predictions for the chance of blacking out against the data."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# define expand grid function:\n",
      "def expand_grid(data_dict):\n",
      "    \"\"\" A port of R's expand.grid function for use with Pandas dataframes.\n",
      "    \n",
      "    from http://pandas.pydata.org/pandas-docs/stable/cookbook.html?highlight=expand%20grid\n",
      "    \n",
      "    \"\"\"\n",
      "    rows = itertools.product(*data_dict.values())\n",
      "    return pd.DataFrame.from_records(rows, columns=data_dict.keys())\n",
      "\n",
      "\n",
      "# build a new matrix with expand grid:\n",
      "preds = expand_grid({'age': np.linspace(10, 80, num=100)})  # put a line of ages in, to plot a smooth curve.\n",
      "preds['yhat'] = fit.predict(preds)\n",
      "\n",
      "# add to data:\n",
      "merged = gf.append(preds)\n",
      "merged.tail()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>age</th>\n",
        "      <th>signs</th>\n",
        "      <th>subject</th>\n",
        "      <th>yhat</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>95</th>\n",
        "      <td> 77.171717</td>\n",
        "      <td>NaN</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 0.994704</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>96</th>\n",
        "      <td> 77.878788</td>\n",
        "      <td>NaN</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 0.995084</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>97</th>\n",
        "      <td> 78.585859</td>\n",
        "      <td>NaN</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 0.995436</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>98</th>\n",
        "      <td> 79.292929</td>\n",
        "      <td>NaN</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 0.995763</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>99</th>\n",
        "      <td> 80.000000</td>\n",
        "      <td>NaN</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 0.996067</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "          age  signs subject      yhat\n",
        "95  77.171717    NaN     NaN  0.994704\n",
        "96  77.878788    NaN     NaN  0.995084\n",
        "97  78.585859    NaN     NaN  0.995436\n",
        "98  79.292929    NaN     NaN  0.995763\n",
        "99  80.000000    NaN     NaN  0.996067"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "g = sns.FacetGrid(merged, size=4)\n",
      "g.map(plt.plot, 'age', 'yhat')  # plot model predictions\n",
      "g.map(plt.scatter, 'age', 'signs')\n",
      "sns.despine(offset=10);\n",
      "plt.ylim([-.1, 1.1])\n",
      "plt.yticks([0, 0.5, 1]);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 287,
         "width": 286
        }
       },
       "output_type": "display_data",
       "png": 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jJS2X9Gwj2z6JU41Aq6usqtGL76zw2u3bpev8kwf6WBEABE+8As/7ksYZYzLa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\ncMPmT+WEnHOtteXu+hflhLafSfp6UPt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       "text": [
        "<matplotlib.figure.Figure at 0x10ddb29b0>"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Logistic regression with categorical and continuous predictors\n",
      "\n",
      "We can extend the design matrix to include any combination of continuous and categorical predictors as in the previous lectures, but using the logistic link function to predict 0--1 data. \n",
      "\n",
      "To demonstrate this I will use a dataset from a psychophysical experiment [(Wallis & Bex, 2012)](http://www.journalofvision.org/content/12/7/6). In this experiment, three observers detected the location of a target embedded in a natural image in a forced-choice paradigm. The target (a circular patch of texture) could appear above, right, below or left of the observer's fixation point. The stimuli looked a bit like this:\n",
      "\n",
      "<img src='pics_for_lectures/stimulus.png'>\n",
      "\n",
      "The image above contains 12 patches of texture (three on each cardinal meridian relative to the fixation point). Note that in the actual experiment, only one patch was shown at one of the four possible target locations.\n",
      "\n",
      "After each trial, the observer responded with one of four buttons. This is a four-alternative forced-choice (4AFC) task: if the observer could not see the target at all, average performance should be 25% correct. \n",
      "\n",
      "We varied, among other things, the size of the patch and the eccentricity (distance from fixation). Let's import the data and have a look:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nat_ims = pd.read_csv('../Datasets/psychophysics.txt', sep='\\t')\n",
      "# columns to lowercase:\n",
      "nat_ims.columns = [c.lower() for c in nat_ims.columns]\n",
      "nat_ims.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>observer</th>\n",
        "      <th>trialnum</th>\n",
        "      <th>blocknum</th>\n",
        "      <th>eccent</th>\n",
        "      <th>patchsize</th>\n",
        "      <th>correct</th>\n",
        "      <th>targetloc</th>\n",
        "      <th>responseloc</th>\n",
        "      <th>imageori</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> TW</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td>-0.391207</td>\n",
        "      <td> 1</td>\n",
        "      <td> u</td>\n",
        "      <td> u</td>\n",
        "      <td>   0CW</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> TW</td>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td>-0.391207</td>\n",
        "      <td> 1</td>\n",
        "      <td> d</td>\n",
        "      <td> d</td>\n",
        "      <td> 270CW</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> TW</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td>-0.505150</td>\n",
        "      <td> 0</td>\n",
        "      <td> d</td>\n",
        "      <td> r</td>\n",
        "      <td> 180CW</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> TW</td>\n",
        "      <td> 4</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td>-0.505150</td>\n",
        "      <td> 1</td>\n",
        "      <td> l</td>\n",
        "      <td> l</td>\n",
        "      <td> 270CW</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> TW</td>\n",
        "      <td> 5</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td>-0.505150</td>\n",
        "      <td> 1</td>\n",
        "      <td> u</td>\n",
        "      <td> u</td>\n",
        "      <td>   0CW</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "  observer  trialnum  blocknum  eccent  patchsize  correct targetloc  \\\n",
        "0       TW         1         1       2  -0.391207        1         u   \n",
        "1       TW         2         1       2  -0.391207        1         d   \n",
        "2       TW         3         1       2  -0.505150        0         d   \n",
        "3       TW         4         1       2  -0.505150        1         l   \n",
        "4       TW         5         1       2  -0.505150        1         u   \n",
        "\n",
        "  responseloc imageori  \n",
        "0           u      0CW  \n",
        "1           d    270CW  \n",
        "2           r    180CW  \n",
        "3           l    270CW  \n",
        "4           u      0CW  "
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Each row in the dataset corresponds to one trial. We are told the observer, trial and block numbers, the eccentricity, the log patch size (log 10 pixels), the target location (relative to fixation), the response location (relative to fixation) and the orientation of the image relative to its veridical orientation.\n",
      "\n",
      "Finally, the column `correct` tells us whether the observer got the trial correct (`1`) or incorrect (`0`). \n",
      "\n",
      "\n",
      "How many trials did each observer do?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nat_ims.groupby(['observer']).size()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "observer\n",
        "N1          17200\n",
        "PB          16918\n",
        "TW          16932\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "So each observer did about 17000 trials. Because ~50,000 observations is quite a lot, the plotting takes a while. For this reason I'm going to take a random subsample of the data first."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.random.seed(12345)  # seed rng so these results are reproducible.\n",
      "rows = np.random.choice(nat_ims.index, size=5000, replace=False)\n",
      "dat = nat_ims.ix[rows].copy() \n",
      "dat.groupby(['observer', 'eccent']).size()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "observer  eccent\n",
        "N1        2         558\n",
        "          4         597\n",
        "          8         510\n",
        "PB        2         527\n",
        "          4         547\n",
        "          8         571\n",
        "TW        2         538\n",
        "          4         570\n",
        "          8         582\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "How can we predict performance across all trials? This is another example of a binomial dataset, which we can model using logistic regression. \n",
      "\n",
      "We can plot some of the data and fit models in one step using Seaborn:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.lmplot('patchsize', 'correct', data=dat,\n",
      "           hue='eccent',\n",
      "           col='observer',\n",
      "           logistic=True,\n",
      "           y_jitter=.05,\n",
      "           size=4)\n",
      "sns.despine(offset=10)\n",
      "g.fig.subplots_adjust(wspace=0.5)\n",
      "plt.xlabel('log patch size')\n",
      "plt.ylabel('Proportion correct')\n",
      "plt.yticks([0, 0.5, 1]);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 293,
         "width": 914
        }
       },
       "output_type": "display_data",
       "png": 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B+rnUdaGvR0REXuAUl0zeB56fccls+/888O6qr18kasS9B3iv67pvaby7iIjImaOYZPI+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ellKq0Gdd+sE4VMnulcnuuHt9mq7XKmOJmFziTIZ51OHDGzY5SjAGf1XeJCjWjjAfJdkpqu27lW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\n/pJUZ2fG17011Uz/wd8SmFBcPK20LTAM/M3n5lpD085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ajVJbW8vq1atZvXo13d3ddHZ2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cz/iUyj0XzjKHYqEmDt5laWv7CVbK6AyAXMm17FLZfMoiTivmgmhERIRVVZmJJIgJyVY29/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i8kB/SM3nG/aHHNu5LFvw3HBX5CiNAxwxq5LLzu4oWefAYHaIZ7c/x9ahbaPOqwiUs+zo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\nDc+Vk3EILRfnasMv2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juS6QK6rjDQFebitRiZ7Ev0zGVxB6wW6AQ9c1n+8bmvM50Zx6kT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\nrkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10dd8c0f0>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# the data get easier to see if we bin trials along the x-axis:\n",
      "sns.lmplot('patchsize', 'correct', data=dat,\n",
      "           hue='eccent',\n",
      "           col='observer',\n",
      "           logistic=True,\n",
      "           x_bins=6,\n",
      "           size=4)\n",
      "sns.despine(offset=10)\n",
      "g.fig.subplots_adjust(wspace=0.5)\n",
      "plt.xlabel('log patch size')\n",
      "plt.ylabel('Proportion correct')\n",
      "plt.yticks([0, 0.5, 1]);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 293,
         "width": 914
        }
       },
       "output_type": "display_data",
       "png": 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PzemZ83OaXtjd9+aToz0ypwdkTg3owbH+Lc0X3FyOtV5BoTV3QlbD\nqq6sXNWl5Uu6tHJZhVpx18+Zz7TrTNfR5NZ9VCc7R5RzGx8DRoWiKs+dVeXZF+VfvCLFrZEER+s5\nmN9AAADYY0EYq1CuqVwNVAtiuWlPpdwWJr8Okqof6tLkii5eX9GF68u6MrkqP2js7sf2NldHj+R1\nbCSv48N5HRvu0JGBDmUy2/+SZK2V9WtSuZTsgowiKZPsgnTadv8FoxYHmvYXNOXPrSUh6zsfAQBo\nRdZaVfxQK8Wa/Fqo2Eq5rHugS8fXy6qVwpKi+EYSMqM7x2FhFGtqtqLxqbLGJ0sanyqpVGlsXJPN\nOBo90qFjw3kdG87r+EheI0Mda+VWk1jFlworipeScnROLrfrcvF+HGiqOqfr1Rld92c1VZ1d2/0I\nADgcotiqWK5ptVRTLYyVyzr7/nkfxbHOjy/r896snjk/p5XizkuxDvV16CVnBvXImUGZ0wPq6dza\nd/ybd0JGch0nLcfaWj0hrbWaK8/pwvJFXVy+pInCpOwul0n1Zjt1f/dx3dd9TPd3H9NIx6DcBu5+\nXC9aWVXl2RdVfvZF1S6PS3ZnY8/096rj4QfUbh6Unvp4g0eJVnNQv48AANB0fhCpUEqSkGFklck4\nymburV2QhXJNF64t6/y1ZV24tqxrs4WdxpCbas+5SeJxJK8To506PpLXQF/brgLitVKsxbIUBEnA\nns0mSchd1Mi11mo+WNZkdU5T/pwm/TnN15Z3/YUAAIBmi2OrcjXQajlJQkrJLshc7uDGLLGNVQ4q\nKgXFm8qquXf4rK8Fsa5Nl3R1oqQrEyVdny4rjBr3OZ7NODp6JIlrjo8mx+HbLKqytZpsoSD5fhJb\nZbO7SkKWo2qSfKzO6Fp1RjP+AjEKABxSfhBpcaWqai1MF0tn1LGP8xRRFMsbX9Lnzs7q6XNzKlV2\nVlq0LefKnBrUS+8f1KP3D2lkYOvlxW/tJe2mOyEb2495t4I40JWVq7q4dEkXli+qUNtdNYPebKce\n7BnTAz3HdX/3cQ219Ta0/OpGUbGkyhdfUPnp55Ik5E5kXLXfd1odjzykjkceVHbkyI0xk5C855GQ\nBABgnWotTMqa+UlfpWzm3uoFuVL0dW58SefGl3X+2tKuS6asl804Ojqc14nRvE6MdGrsaF6D/e0N\nWY1no0i2XJbKVdmgJjlOMqm3i16Q1cjXpD+nieqcJtPSZjW7+54MAADshXoScqVYkx9Ech0pl8sc\n2FKsUrI4yA99FYKianFNruo7GjbfEeHXIo1PlnV5oqgrEyVNzpYbViHMcaSRwY4krhnt1InRZOfj\nnfpY2yiSLRSlclk2jqVcTk42t6NYpRxVNV6Z1rXqlMYr05oPlnf+x6zTVot1arY5vb8BAM1jrVWh\nHGil6CsIY+Vyrtr2ceFRHFudv7akp16Y0Re8WZWqO9ulPzrYqZc/cEQve2BID4z1r1UY2NIYbKxy\nrbzWE/JGErK1yrGWg7IuLF3U+aULurRyWWG884oGnZkOPdB1TA/2jOmh3jEdae9ragJSkuKqr8qz\nL6j89PPyL1ySdtD70+3uUsdLHlL+JQ+r/aH75Xa0N2GkOAgO7jcVAAAapOonk3mVWtLwPZu7d0qx\nrpZqaQJySd7VJc0sNi4BOdTfprGjnRob7dTJY513naTbLhtFssWSVKnIhqHkukkvyB2UYrXWajks\naKI6q+vVGU1UZxs2sbdeX7ZbR9uPaLRtUKPtQzqS7dcTn/vThr8OAOBwstaqVAm1Wvbl1yI5SpKQ\nB716Qy2qqVAryg+Tfo5ZN6uce+tuwloQa3yypMvXi7p8PU1ANmiTYE9XNolr0tjm+Eh+S++rtVa2\nUpEKRdkgSErH76B3dSXyNV6d0nilsQlISTpRy+tlU67GxovqmliUE8f6n6avYc8PAGieKIq1VPBV\nLCelT/fzc99aqytTq3rqhRl97uzMjsqxuq6jh0726xUPHtHLHjii0cGt74Ks80Nfq7WCapEv13Hv\nuHhpv6z4K/IWz+nc4nldL0zsuKpB1s3ovp4TejB/TA91HtPxnlFl3Obv+rRRpOq5iyp/7ouqPO9J\n4faTqNmRI8o/atTxUqO2U2Ny3DtHR7aR5brQskhIAgAOpZt2Qt5DSciKH+r8+JLOXl3S2auLmpwr\nNeR523KuTqSJx1PHkom6znzjw4gbSciybLjzfpCxjTVXW9K1tLTZ9eqMSlGloWOtJx+Ptg/paNsR\njbYPKZ+5eZVfFLEDAQCwe34QaXm1qrKfTAa15TL7uiuiEWpRoGKtKD+qKraxsm5O2Q29naLI6vpM\nWZeuFXX5elHXpsqKGpCBdF3p2HBeJ4916eTRJLbp69lerGHDUHa1IFUrsnK2vWgqiENdq87oamVS\nVytTmqktbPfP2FTOyep4+7Dur3Tq9LWyei9MyZm+2pDnBgDsnVoQaWGlqoofKptx9rUM+/xyRZ95\nflqfeW5Ks0vb/17d3pbRo/cP6bGHhvWyB4bU2bH9EuaxjVWsFVUKyorjSNlMruWSkAuVRXmL5+Qt\nepouzez4eUa6hvTI0AN6qOOozmSH1J7JysnuTRqnNjmt8lNPq/yFZxWXtr+gPTd2XPlXvET5Rx9R\nbuTIHc8N40ixjeXIUcZxlcvkdHImmN/p2HEwkJAEABwafhAlSchqqCi2yt0DScgoinV5alUvXl7U\ni1cWdWVyVXEDVpX1duV0+kSnTh3r0qljXRo50qHMXVaz7dRaOdZSWTYMpEzaD3Ibqz4jG2nKn9e1\nyoyuVac1UZ1taPnVTrdDxzqO6Fj7sI62H9Gx9iPqzHTc8RpbqSi+ssOeCgCAQy+KYq2UaiqUamtx\nS6smIW1aJ9W5y4r9MA5VrBVVDquyNlbWzSrjZlX/q6y1Wlj2dXG8qAvjBV25XpIf7L4Ga0ebq5PH\nunTqeJdOHevUidFOteV2trsgrlSk1UKyGzKb3XJJ1tjGmqkt6kp5UlcqE5qozirS7v+27kynxjpG\ndKJ9RKcKOfVfnJb1zsvOMZ8HAAdRqRJoqeDLr4Vqa9u/3ZCVaqjPnp3RZ56b1oXr29+135XP6bGH\nh/XYw8N65PTgtkqxrhdEgVb9VVWj6lo/6YzbOvHQYnVJZxfO6sWFs5otz+3oOXJuVg8N3aeXjjwk\n039G/b6juFKVk8nK2YMemHG5ovIXnlXpqacVTExt+/q202PKv/ylyr/8JcoO9m/+GjZWZGNZK2Wc\npCR/d1u38tm2pEe4k/ydo0thY1eSo+WQkAQA3NOCMNJKsaZSJUgm87Kusln3QH8Azi1X9PylBb14\neUHe1SVVa7vfhTc80K7TJ7p0+nhy6+vJNbUPgY1j2Wo1LW8WSm59Z8HW+gjUE5BXK1NrCcjQNmY3\nYsbJaLRtUMfbh3WsY1gn2ofVm+2+6/th41h2ckrRxUuKL12WnZyWrJXMfQ0ZFwDg3hTbJCnlOu5a\nSdaVoi8/iJTJOC0dt9gw1OJHPqzS3/+d5DjqevVXaPBb3nnTKv7YxirVSiqFJUVxpIybVdbNSGka\nsuJHujRe0IXxoi5cLWiluPsFRT1dWZ0+3qUzJ5Ik5MhQx656Wts4TnpDlkqy1srJ5ba0G7IQlnWl\nMqFL5QldrUyqEvs7HkPdQK5XJztGdbLjqMY6RtWzVFX84lnFLzwpu7DYgBQnAGCvWWtVKNW0VPAV\nW6u2XEYd7Xv/6W+t1bnxZT35xUl93ptVEG7vU6WnM6fHHh7RlzwyoodP9e+qtGg5qKhQW1UQh8q5\nrbUbcsVf0YtpEnKnOyH7O3r16MjDeunIw3po6IwyoVW8uKx4yZfN5eTuoFXNdlhr5V+8otJnPq/K\ncy9K4fbmU3Jjx9T5ypcp/8pHlR24tQx8ffejHEc5J6P2TJvy2Q7lMrmWSihj77Xq9xoAAHYsiq0K\nJV+rpUBhFCUTeS08mXc3tSCSN76kFy4t6PlLCzsqkbLR6JEOnTnRpTMnunX6eJe6O/fm3YmrvlQo\nyPo1yVE6oXf3ci2xjTXtL+hqZUrj1SlNVGcV2J03gl+vN9ul4+3DOp7uLhhtH1TG2VqAbEslxRcv\nK7pwUfGlK1K12pAxAQDufWEc6fEvfFRPjn9OkvSqkVfqTae/Qa6blGM9CH0hFz/yYRX+1xNrv9d/\nHnrXt6sa+iqk/Z0cx1XWzcrNZBRbq4mZss5fLejC1YKuT+++D2Rfd073jXXr9IkkCTnY19aQhVU2\nCGVXV2Sr/o1e1nc4P7KxJqozulS+rkuVCc3VlnY9hqFcn07lj60lIbuznYoXlxQ//aKiF/5SATsh\nAeDAimKrlYKv1VKyYGW/yrIuF3w9+eyk/vaLU5pb3t58Q2d7Vq8yI/qyl47uOglprVWpVlIhKCq2\nsXKZnNpaJBFZDio6u3hWz829oInixI6e40TvUb1sxOjlo4/oRO9ROY6jyPcVzSwqDAI5uZzc9ub+\nvVGprPJnn1bpM59XOLe9cvHZ4SF1vurlyj/2MuWGh9but9YqtLGsjeWmMV93W7fyuTZlnWxTF7vj\n4Dmoc7MAANyiUg20VPRV9SNl3GRHQSbTvI+6rZYn24m55Yqeuziv5y4muyDDaHfr3UeGOnTfWJfu\nO9GtMye6mtL/8XZsGCa7CiqV5D3bQhLSWqv5YFlXK1O6WpnUeGW6ISVYHTkabR/SifaRpLxZx4h6\nsl1bvt5aKzs9o/j8BUUXLslObr+cCQAAkvT45z+qT1z89Nrvf3X9ScXW6p+ab9rHUW2djeNkZ+QG\nxb//O1Xf8kbJscqmOxqqfqSz48s6f6Wg81cLKpZ3t6iopyur+8e6dd9Yt86MdWmgtzEJyLqbyrLm\ncnJyt49bimFZlyoTulS+rsvliV3HK4O5Xp3qOKZT+WM61XFUXdm8JMkWS4q+8KL8556X3UE5NUly\nxk4o8/BDcs2D0p9/alfjBADsXBxbLRd9rRSrcl13X/tD/pePP6/nz22v9Usu6+qVDw3r1S8d1Uvv\nG9pxOda6ejWFQlCUlMQPGe3/wqwwDnV2/pyeX3hBV1avrFW12CpH0v2Dp/WK0ZfoZaNGQ50Da49F\nVV/R4pJsPRHZxB2R1lrVrl5X6cmnVP7iC1K09d2QblenOh97mTq/9BXKjR2X4ziKbaxaFEqyyjgZ\ntWVy6sm1qy3TnlbBAG6PhCQA4EALo1irxWQ3pLVJf6Vm7yjYSnmy7YriWJeur+iZC/N67uK8phe2\n3zx8vYHeNt1/slv3n0wm6/ZqB2SdjWPZSkUqpiVZs9m77ioohmVdqUyu3UrR7neC5pysjneM6GTH\nqMY6RnWs/Yja3LvvyFzPBoHiy1fTJORFqVDc9bgAAIeXH0SaXy7rr69+9pbHnp59Rt/08D9e66PT\nyuJqRXGpdMv9tlRSthZqsebq7KV5eZdXNT5VUryLtVUd7RndN9al+8eS2ObIQHvDV9tvtSyrtVaz\ntUVdKF/ThfI1Tfu726HYnenUmfwxnc4f16n8UfVmu2+8VhAoeu4FRV98TvHlK0kp+O1wXblnTsl9\nxCjz8INyurvvfg0AoGmstVot1bS4WpXrOGrL7f/U/LMX5iV79+/IjqSHTw/oKx49qi8xIw0pKRvb\nWIVaQcVaSa7jKOvu//sRhpGuFSb0wsIL8pY8+dH2yq27jquHhs7oFUdfqleMPqKe9ps/e+NaoHB+\nQTYI5eSyzU1EBoHKTz+n4t88tb3ekBlX+UcfUeeXvlId5gFZ11EURwriUFkno/Zsm/rbO9SWaZPb\nhAX6uLft///LAQDYpnp/peWir1oQKptxlWyEdPakFMSdypNtR8UP9fylBT17YV7PXpxXubrz3QL5\n9ozuP9mtB04lE3WDfVvrxdhoNghkVwtJf0jpjj2WgjjUteqMrlQmdLk8oflgedev3+G2aSwtaXay\nY1Qj7UPK7GBS15bKis5fUHzuguJLl6WwMeVhAQCHk7VWhXKg5YKvMIoVyVc5vHXxUSkoyw995XP5\nfRhl4/zaR85rsrDz6zOuo5PHOvXAqR49eKpbx4bzct3mxHg2imSXV5LY5f9n7z2f5LrONM/ftemz\nvAXKASh4bwmAlEBKNGJ3j1qtduqe/rKxmpne3ujYv2A3Yr/txH7bjZ2O0UZsdO/stNGoZbpJiaJI\ngCK8LXgPFFBAeZs+8957zn5IFAgQqEpTWVUJ8vwiGAGgrjlZVcH73vO87/PMYcvqSo+H6SFuJx9y\nNzVA3Cu/cczWTDoCbXQH2ukOtNNg1TxXv0opkQ8f4V26jHf9JuRypd3AMNBX9WCsX4u+dg1a4NX+\nXVIoFIqvCsm0w9h0/vlhL+NEZKm01AfZv6WNvZtaqY/6K3LNZ4VIQ9OxjNKahiuJlBLH9Ujk4lyf\nvsHV8StMpEuzXNc1jd6GHra3bWJrywZCdvDF+7gu7sQUIp1Bsy30IqJrysWdniF5/AzJU+cRqeIb\nvc3WZkJ7d+DfsRkZ8KMBUtPwGzZ+fwDbsF6JpjlFdaMESYVCoVC8MjzNV0hlkTJfxJumxk9v/4wL\nIxfRNNjevI3v9X530UKy57InS545Rf0P/m1B+9bpeJZLd8bouzXGzQdTeGWGJmkadD7dqIvQ3rx4\nG3WFkFIiUymIJ5CeC+bLrc2klEw6M9x7IkAOZIZxZWnB6V/Gr/vo9LfSEWil099Kk11XtigtpqYR\nN2/h3byNfPS49CmEWXw+tJ4uzDWrsFb3UPur/6rCnRQKheJriusJpuNZ4qkcGvlsKMMwSDuvdpZO\n2kkznRyb8+sT0zkoMfOpodamtyvCmq4IXe2hxXe8cFzkzBMh0jRfqF0yXpZ76UfcTj7k3gKtWFvt\nBnqCK+gJrKDd3/zSZik5E8O7eBnv0mXk9ExpN9D1vAi5cT362l40//I0pikUCoXiRRzXY3QyTc7x\nsJc4H9r1BOdujPLp+buwovjzfLbB7vUtHNjaxqoVNRVr/BZSEMvGSDop9GUUIl1X5C1qpeBhsp/L\n45e5OXEXSfF7ALN2rDvbNrOtdSNh38ujYKTr4U5O4aXT6ObiZkTmHg0S/+wE6UtXKTagW7Mtgju2\n4N+zHX1FK6aen4AMmmoCUrE4KEFSoVAoFFWP43pMzmRIZlwMQ8Myvyjif3r75xx7fOLp32f/vFj5\nS3PZk4lEApFJYwRfLEJHJlNcuDnKxdtj3B+MlX3vaMiktztCb1eUVR1h/L7l7aqUnpe3NkslkfLJ\nNKT+fHHtCJeHmSHuph5xL/WIGXdhdqe2ZtEZaKXT30ZXoG1BAiSAGB9HXL+Fd/MWcnik7OvoLc3Y\n69YQ2NCLv6sD40nHq+d5mHpuYQGgCoVCoXjlyDoeEzNp0lkXy9RfqUmI+Ug5KUbjU9y4N8O9W5O8\nvzKrPH8AACAASURBVIBr2ZbOqpVhervzzVV1NYu3Qfcs0nGQU9PIXO5JrvUX9026aW6nHnIz2c/D\n9BCihI3JZwnoPnqCK1gVWEl3sJ2Q8fIpRem6iFt38Pou5R0ZSkHT8nasmzZirFuLFqjM1IpCoVAo\nKoMnJBMzaRLJHLZtLKkYmUg7fH7hMUfODzCTyIHhEChCkFy1ooaDW9vZtaEZv1052WC5hUgpJa6b\nfy03LQNHi9M3fomzg5dI5F7c35mP9kgLu1dsZWfbZmoDNXPfUwi86Rm8eBLNNDAWyZpVCknm+i3i\nvz1B7t6Dos8z21oI7NtBYMcWfMEwIcuPbaoMSMXiowRJhUKhqFLEk26m5Zp6qwaSaYepeJac4700\nG1JIwYWRiy+ct9z5S1JKBseSnL85yoVbowyOlVbgzqJrsLI1wNqeKOt6amiur3xeUjlIx0XGZpDp\nDBgGmmk9Z20248S5kxrgbuoRDzPDeAuYgjQ0g5W+ZroC7XQF2mj1NSzo5yqlRI6N4127gbh+Azkx\nWd6FLAtf7yoCG3oJbOjFqImWvSaFQqFQfHVIpBym4xlyrodtGRXdzFsupJSMxmY4d3OIa3dnuD+Q\nwhMSn5crWZBsqLVZ2x2ltztCd3sI01y6Wk26bl6IzGafEyJjbpJbyX5uJR8wkCm/OanFbmB1cCWr\ngitp8zXOW6+IiQm8CxfxLl2BEqzUALS2VozNGzE2bkCLqExIhUKhqEZmElkmYxkMXcNXgazFYhme\nSPLp2QFOXB7CcYvrizVNyWtb2ji0s4OVzZGKrmc5hUgpJK4n0DTwWSaRqMmtqTuc6D/HrYl7JV2r\n1h9lV/tWdq/YSlukueDxXjyBOzWNpuuLZs0qXY/U+UvEjxzDHZso7iTDwL9tI5EDe4j2rCboC2Dp\ny2eXq/h68uq/HSkUCsVXDNcT/Ohnl/m87zGg8cb2dn74+1swja+HTYIQklgyy0wih5AS2zLmtOzK\nutWVvzQ4luD8g2HO3xhlZLK8bKGAz2B1V4i13WHWddcS8FfPo1rmHOT0ixMFQgoGs2PcTQ1wJzmw\n4CzIFrv+Sa7SClb4m7EqEGwvRsfwrt9AXCtfhDRqovg3rs3/t7oHzaqen41CoVAolg8pJbFkjul4\nFk8KfJaJ7ysgRMZTOU5dG+D8zTHuP0qW5WSu69DVHmJdT5R1PVEaapfeSvRpRmQ6/bR+iblJbib7\nuZno53F2tKzrmppBd6CdNcFOVgVXEjFfzIt6bh2um7eGP38R8eBhaTeLRjG2bsLYsgm9oaGs9SoU\nCoVi8clkHUam0sgnexlLxd1H03x08gGX7pSeFmJt/oyhmhZqan9YsfU8mxG5VEKkFALhCTw0DE3D\n7zepD/hJuQmOPTzOqUcXiGWLd2yyDYutLRvYs3IbvQ09RTVGe5ks3vgEUgj0l8TYVAKRzZE8dY7E\nb0/gzRQX2K3XRIke2EPz668TrK1XOZCKZeXVf0tSKBSKrxg/+tllPjze//Tvs3/+y+9vW54FLRGO\nK5iKZ0imc+iavqQd85Xif/8v58mWmJcE0Fjno7crTG9PmO72SNWJzyKThZkZpOvk8yFtm5xw6E8N\ncjv5kLupAdIiW/b1w0aA7sAKeoIr6Aq0zWlrVvK6J6cQV6/jXbuOHCsvxtFqb8W/aR2BTeuw2lur\nYkJVoVAoFNWBEJLpRJaZRPZpPqRJdT3DSyWZcTh/Y4Qz14e4/TBWdpzypt4aVq9tYk1XhMAyWcxL\nIZAzMWQyCaZJUne5EbvDjcT9skXIkBFgTbCD3lAnnf62opqm5PQM7vk+vL5LkCqhYc22MdavRd+6\nBb2rQ9UgCoVCUcW4nmB0KkUm6y5ZU5KUkit3J/jo5APuPFpAU7DhMZgY5G/6fsRf7/orfGXsaTy7\npkQuQSwXx1giIdLN5nB++i/IvotomkZo304a/uKPuBsb4Od3TnN55EY+L7JIeuo62LdyB9vbNuE3\ni2ukkq6HOzGJyGTQbRvNqHztI1JpEkdPET96Ku9WVQT+nm6a3/omDdt3LMqaFIpyUIKkQqFQVBFC\nyCeTkc/zed8g//57W7+S9q3pjMNkLEvW8Z5kLH09Hk1dbWF6e0L0dgdprg9iVJlPv5QyP0kQiyM9\nD82ySOuC2/Hb3E495EF6ELdMK1YdnQ5/Cz3BFfQEViw4B/K5dcfieNeu4129jhwaLv0Cmobd00lg\nywYCG9dh1tdWZF0KhUKh+OrgCcl0PEM8lUNDe+XzITM5l0u3xzlzbZhr9yfxRJkq5DN8962VaMGl\ndaqYRUqJjMUhkSAlc9zKPOJ64h4PM2XUBUC9VcPaUCe9wS7afI1F1SxSSsT9fryzFxC371CKsqt1\ndmBu24K+Yd1z+ZYKhUKhWF5eFqsjpWQqlmEqnsO29SURI4WQnL0+wkcnH/B4rMiJP7NwA/FQYojD\nD4/wXs87Za0rkUsSy8XyTVqLKER+kQcpsSwT/YMPkcdP5L8GJD79nAvDV/hwe/FrCNsh9qzYxmsd\nO2gJN5W0Fm8mhjcTRzMN9EV4bnvJFInPT5I4dhqZKaIRXNep3bGNlm+9Rai7u+LrUSgWytdj11eh\nUCheEVJZl3jKeeHf46kcqaxLOPDV8HZ/zpZVyJfmQ1Yb0/EsZ6+P0Hf5IX9Yxvm6prG2s5b1qyP0\ndPoJh4wlD3IvBul5+U28dAopIUaGW6mH3E4+4FFmFEl5m5QRI/Q0V6kr0IZdwZwCmcni3biJuHy1\ndAs0AEPHt2YVgS3rCWxajxEOVWxtCoVCofjq4In8pmM8lcXQdSyzumuX+XA9wbV7E5y6OsylO+NF\n50w9S0NtdYllUkpkMokzNcWtzADX0/3cTz1GlFG7tNoNrA11sTbURYNdfHOSzOXwLl7GO3MeOVmC\nRXw4jLF1M8b2Lej19SWvtxBCCITIV3E6oJsGAS1VvG+dQqFQfI2ZK1bHdT2GJ1NoaPiXwA3A8wSn\nrg7zqxP9jE4Vlz+sBeKYrf0YDYMFj5VI+kYu8W732yU1DGfcLNPZKYSQmMbiSA1SShxXoD/Jg6yt\n9WFbBhqSh2cvvHD8yrvTsK0RCnyOdY2rOdC5i83N60puEvdSabyJKdBYlJxIL5Ek8dsTJI6fQWZz\nBY/XfT4aXz9A06FD+BoqX0ssNtLzEJ4LUNz4p+KVRQmSCoVCoVgyPE8wncgSS+bQNTCrfCMvk3W5\ncGuMU1eHuflgEinB5xUuBGcxDY0N3Q1sXVtPZ4eFaQl0Ta+6aUgA6Tj5fKVsjkmZ4FZqgJvJfkZy\nRYajfwkNjRX+ZlYHV7I62EGjVVtRqzHpeYi79/AuX0XcugNeidOahoF/7WoCWzcS2LQOPeCv2NoU\nCoVC8dXC8wRT8exTIfJVdXOQUnLv8Qynrg5z7voIyYxb8jVaGv1sXF3DpjU1NPoFmRf3AJcFN5Wk\nf+gG15L3uZV+iCNL/2wrfM2sC3WzNtRJjRUp6VwxPYN39hzehUuQLd7GXl+9CmPndvTe1Wh6Zex+\nPU/kxVnA0DQMUydgG/hsC9MA/cl9Qlo8WZEbKhQKxVecl8XqpDMuv39o9ZJMRDqu4OSVIX51op+J\nmeK0mp6OAKPhE3jh4UKa3HNMZ6d5EHtAd013wWNd4TKVmSLnOViGRaW3OaSQuJ5A08Bvm9RF/C80\nsj8YvIdIvPg4C2QltiPJ2S9++LAdZN/KHezv2EVjqHThTnoe7tgEIpdblJxIkUoT/+0JEp+fROZe\nHFj4MmY4TPNbh2j8xhuYwfnzrKsN6XkI10UzTcxwGH80wsGf/2RoudelWFxezTcphUKhULxSOK5g\nMpYmmXYxjeq2NvOE4Pr9SU5eGebi7bGSJwZMQ2PTqgZ2rm9mTVcQR0vjCg9L19G06vvcIpvPhxxL\njnMz+4hbqQeM5abKupZPt+kJrGBNsINVwRUEjMqKfFJK5PAI7sXLiKvXIV1cV+hTDB3/2jVKhFQo\nFApFUXwxEZnD0LVXVogcm0px8sowp64OMz5d4rMTaG30s6m3hk1ramms+yJLSaZKv1alGZkZ5PLj\nC1xL3CUpSm+oX+FrZn24m7WhbqJm6Q4JYuAR7qkziJu3i7dlDYcwtm3F2LENvbam5Hs+i5QyL0Ai\nMTQdw9QJB6x8nqmufSXjHhQKhWIpmStW5/T1Ef7o7bWLem/PExy/PMQvj/czGSv8jNM1jT0bW3hn\nXxePvRv8/fVhSn0KZL0sY6mJeQVJIQUzmRlSbgpTtyrq/PTsJKTfZ1Ff439h/0hKyfWx23x67zgP\nh+/xl0Vee1VdJ6937WFry4ayJzndWBxvaiZvz1phMVJksvmMyM+OF2XNatfX0/L2t2jY/9qiWMUu\nFlIIpOuAbmBGwvgjkUURdhXVy6v5RqVQKBSKVwLXE0xMp0lmHCzTqGpb1sejCU5cGeL01WFiyeKn\nIJ/lz99bz8aN7bhampSTIksSU7OwqzA8XKTTTIwPcD1+j5vph4w702VdJ2qG6Q12sCbUSYe/FUOr\nTHf/s7gzcbwrV5GXr8B4iRObmoZvTQ/BHZsJbFqPvkx5VgqFQqF4dXhRiKy+53ghUhmHczdGOXll\niLuPZko+v7nBz+beGjb31tBYV10NPEknyZXRq1wZucRorgRb1Ce0+5pYH+5hXZkipBQCces27snT\nyEeFLfBm0To7MHfvRF/Xi1ZmbSg8gSclGhLDMDANnWjQxjK1p5OPCoVCoagcc8XqJNMOmaxL0L8I\nVp1CcPrqCB8cu19UI5Fl6ry+rZ1v7emksTb/vvt4kWbMUk6Kqcw0uqZjGZURwWYzITWeTELWvTgJ\nCfmJzPODVzh87zhDiVEACq3A0k12rdjK6117WBltK3+NjoMzNoF03Yrbs0rHJXH8DPHDRxHJVMHj\nfc1NtL73LvV7dpddTyw1UkqE46BpYIRCWNEmDJ+v8ImKryRKkFQoFApFxXE9wcRMfiLSMpcm2L0c\nEmmHM1eHOX5pkIHRhcfodHeZzLgT6JqOWYX5kAATsRGuD17kRrKfsTJFyBa7nt5QF73BTprsuopa\nsUJ+s811XbR795GXryLu3AVR2qSq3d1BcMcWAls3qkxIhUKhUBTFlzMiXzUhUkjJrQdTHLs0SN+t\n0l0e6qI2W9bVsmVtLS0N1SVCesLj3vQ9Lo5d5u7UPQSlfbZmu54N4R7Wh3qoLdGOdRbpOHiXruCd\nPIOcKtJNwrLy2ZC7dqA3N5V2PykRXv6T6oBhGgT8Jj7bxDK0itdfCoVCoXgRWez0ewUQUnL+xij/\n8vk9RiYLC1N+2+DQrg6+taeDSPB5aa4p2IjP8JH1ircRB/AZPpqCDS/8uytcJtKTeMKt2ESk63hI\nJD7boq7Wh20bL322Zd0cJwbOceT+CaYzsaKv/37vm+zp3UfILt/GVEqJNzWNF0+iWWZFJ/mkEKTO\nXyb20WG86cLNY76WFtref4+6XTsrZvO+2AjXQQqJ4fPhb2nGCARU/aJQgqRCoVAoKofnCSZiGRIp\n54kQWX0beUJIrvdPcuzSIJduj+F6pb1gdLVF4P4c15YCq8I2pZUglo1zfewq18auMpwtLxNypb+F\ntaEu1gZLz1UqhBQSTwhAos3E0C5dgotX8F6SBTEfZnMjwZ1bCO7YgllfV9E1KhQKheKrixCS6XiG\nmeTSZERmvRy/6f9kzq//pv8T3ln1Dr4iJw/Gp9OcuDzEictDRVm6PUs4aLJ5bS3b1tXS3lx9m0Tj\n6QkujV7i8vhVUk7hzdlnqTHDbAyvYmN4NY12bdlrkJkM3tnzuKfPQaq4NWi1tRh7dmJs24rmL24C\nYLYems1+tEwD22/hs3RM49XYeFQoFIqvEqmMw8BI8QJYuUiZ36P46ZG7DIzECx4f9Jm8taeDN3d3\nEJpjQrM72kWdr5bh1EhJa6n11dIV7Xr691l71qSTwjKsBTdee66HJ8FnG9RFAwT8LxchAVJOmqMP\nzvBZ/0mSudJqAIA3uvdhLECM9DJZvCcOTZWcipRSkr5xm9iHn+AOjxY83t/aSuv771G3c8crIURK\nIfLTkJaJXVeHGQq9MpOciqVBCZIKhUKhWDCeJxh/MhFpmlpVCpETM2mOXRzkxOUhpuKldQk21wXY\nt6mVPZtaafBJBo6//Lhq2sRLuxluTNzg6tg1BhKPSj5fQ6Mr0Ma6UDe9oU5CRuWsTp/t+Dd1HQsP\n3907ZM71kbv3oKRr6eEQwR2bCe7chrWitap+BgqFQqGobvJCZPaJELk0GZHxXJy/6fu/GUzMbfX5\n6cBn3Ji6zX/Y/kMidvilx7ieoO/WGMcuDnK9vzTbUtvS2bA6ytZ1dazqCGNUWc5gzstxY+ImfaOX\neJx4MbdrPvy6jw3hHjaGV7HC17ygukAmErinzuKduwC54uz89a5OjL270XtXF9w09DyBeMZ+1bJ0\noraNZeoq+1GhUCiWESEkY9Mpkul89Mxi0j8U46dH7nDzQeHJ+5Df5O19XXxz50oCvvlrFk3T2Na8\nhZH+USTFNWFraGxv2fr02Tlrz2poOrZZvj2rEALHk9iGTiTkIxSw5n3OJbJJDt8/wdGHp8m65cXp\nLAQpBO7EFCKZQvdVLptRSkn60WMSH3xC7m5/weN9TY20vv8+9Xt2vRJCpOfk0MhbsvpbW1QupGJO\nlCCpUCgUirKpdiHS9QSXbo9z9OJjrt+fLLIMzxMKWOzZ0MK+za10t0XRNA1PeExPDS/aeheKK1zu\nTN3l6vg17kzfRcjS7Mx0dLoD7awPd7Mm2EnAqJynv+d6TyzH8llcfr+NPjVB+vQ5kucuIdMlTHQY\nBoFN6wju3oZ/7WrVbadQKBSKkplJZJmMZdC1pcuIzHq5gmLkLIOJQf6m70f89a6/em5ScngiydGL\ng5y8PEQi/WKm1VxowKqOMNs31LFhdQ22VX0bW8PJEfpGLnJt4hpZr/gNSB2d1cGVbI6sYXVwJYa2\nsJ+nnInhHj+J13cJPK+IBejomzZi7tuN3try8ms+Z7+qYVo6Yb+JbZuYyn5VoVAoqoZk2mF0KoWh\na/hsk1Sm+GdtKYxNpfjpZ3c5f6PwhFzQZ/LtvZ28ubujoBD5LG92vcnl8WtF1R0AbeE23uw8VBF7\nVikljiswNI1QwCQUsDHN+WuPeDbB4fvHOfrgDDmv8PfdNiwOdGwGPiprjS/DS6ZwJybRdL1iYqQr\nPNyZGOmPPyd5tg8K2ABbdXW0vf8eDa/tq/q9Dul5SM9Fs238TU0YwaCqaRQFUYKkQqFQKEpGCMlk\nLEMsmatKIRLgX4/e4/TliZcG0M+FoWtsXt3I/i1tbF7d8NQeK+c5zGRnyLpZDLE4LyTlIqXkUfwR\nl8evcmPiRkkbeJDfFMuLkD30BjvxV0iEzHf9iyebbgbhoI3fZ6ALQfrKDeInzpY8DWl1rCC0ZzvB\nbZvQg5Wb2FQoFArF14d0xmF0Oo2UcskzIg8/OMxQYqjo44cSQxx+eIRvdXybvluj/PbCY24PlJb/\n3FTnY/uGOrauq6UmUrku/0qR83Jcn7jBhZE+hpKlNX21+hrZHF7NhvAqghWwzBdT03jHT+JdvFxc\ndrXPxti5HXPPLrRo9LkvSSFxhYeGhv7EftXvt7BtHeMVmHJQKBSKrxuekIxPpUhm3EXd30hmHH55\nrJ/D5wbwxPzClN82eGt3B9/e20lwDmvW+fAZNv9h+w/5m74fFRQl28Pt/Ltt/z2pXHJB9qye6yEk\n+GyTujofPruw9BDPJvj03jGOPTxblBAZsoN8o2sfr3ftwe/AwwoIktLzcMcmELlcRSb7hBS4QmC6\nHu7xC0z+5jCigNuCEQrS+t67NH3jjaqeLpRS5i1ZNR0zGsaKRtFNJTEpikf9tigUCoWiaKSUTCey\nTMezTzoGq0+InOWTswPgFVfErWgKc3BbO3s3thB+Jgw+5aSJ52K4wsPUTWzTRuaK6JRfAiYzU1wZ\nu8LV8WtMZwsHoD/LrB3r+lAPa0NdFZmEFELgCYkOGKZB2G/i85lPRV13aobEkbMkT51HJIvPf9BD\nQYK7thLaswOrtXnB61xKhBS4nosuKW1UVaFQKBQVx3E9RifT5FxvyYVIyNdQF0cvF22bBuBl/Hx6\nfJzfTBwlUUKDlc/W2bK2lh0b61nZUn25kADjqXHOj/ZxZewqWa94K/2g7mdTZDVbIr002ZXJixaT\nU3jHTuBdulJwagGASBhz726MndvRfPkaSngC7xn7VdvSqbHz0yDVZL/qCBcpJYZmUBv3Esu9HoVC\noagGMlmHoYkUhrF4exyuJ/js/CM+OHafVMad91jT0Hlz10re3d9NOLAwYSpih/nrXX/Fr+9/zKcP\nj7z0mLc6D/GNjjdIOkl0KNmeVQqJ43mYulGUJessiVyST+8d4/P+0zhi/u8JQK0/ylurDvJaxw7s\nJ+4RXon50i/DiydwJ6fQTHPBQqDjuWiA3/Rh3rzL8E9/QW5yfjtezbJofutNWt/5Nkagehuvpech\nXBfD78ff0owZLD+fU/H1RgmSCoVCoSiKeCrHxHQGTVv6iYLFIOgz2bOplYNb2+hoiTzdrJNSknJT\nxLJxhBRYhoVlVEcne9bNcmPyJpfGLvMoXlqmEsAKXzMbw6tYF+omZC6s0JVS4nkCSf6FKWAb+HwW\n1jO2Y1JKMrfukTh+msy1W8Vt8gFo4Fu7hvC+nfg3rEVb5NyOSuEJgSc90DQszcBv+qj1Rdl2Kz2y\n3GtTKBSKrytP7eVTDrZtLFsN0x97wFS2uOlGb6YBd7gbMdNIFg0oTozsWRli58b6JbFkldksuY8/\nmfPruY8/wX7v7aeCHYAnPG5P3eHcyHkexgaKvpeGxqrgSrZGeitiyTqLmJrGO3q8aCFSq6/D2L8P\nY8smhKbjSonmehimQcBv4rPN5+qgasAVHkLK/JSmblHni2KbPkzdYM2jXGy516dQKBTLiZSSqViG\nqUQO/yI2W1++M86PP7nF6FR63uM0DfZvaeN3X19FfXThk/+z+Aybb3e9NacguatlB4lcomR7Vsfx\n8uKb36Kx1o9Z5Ht7yklz5P4JPrt/siiHp6ZgPd9a/Tq7V2zF1CsnZUjXwx0bRzguul2+i8TsPoCt\nm9QFamBsisc//i/Eb96a/0RNo+HAa7T9zvvYtbVl33+xyWdDapjRCIGamqq3kVVUP0qQVCgUCsW8\nZLJ5azPPqx4hUkrJ3cczfHr+HoRLO3dtZy2vb1vBjnVNzwXUSylJ5pLEnARIiWmYGCz/55VS8iD2\nkEtjl7k5eQu3iM7BZ2my69gYXsWG0CpqrBK/WV9iNgfSeGI9Fg3aWC/p/BeZLKlzF0kcP4M7Ol70\n9Y2aKMG9Owjt2YFZV7OgtS4FrvCQUqIBpm4RsgIELD+mbn4hygqBqeYjFQqFYsmRUjIVzzKTyGAY\nOr4SMpcWg7HUeNGTgLk724t2eQgHTXZsrGPXxnrqayuX/TwfMhYn859+hHw8t/2b98kRMjdu4f8f\nfkjSp9E3epELIxdJOMUP5dWYYbZG1rIlsoaIGarE0oEnGZHHTuQzIouwZtVaW9Bf24dcuxpNN9At\ng6CpY9smVoE8rKXGFR4CiU5egIzaAfyWr6IbuAqFQvFVwPUEQxNJhBCLJkYOTyT58Se3uXpvouCx\n29c28d1vrKatsXLPu2LJCYegVdy0m/DyVqS2aVIfDRDwG0U34mTdHL/tP8mn946TdjMFj28NN/HO\nmm+wvW0TulbZ562XTOKOz05FlveMdDwXTdMIWn7Cdggt6zD0818yeuSzgvVFZMN6Vn7/ewTa28u6\n92IjhUC4DrqlsiEVlUdVpQqFQqF4Ka4nGJ1Kkcm62JaBscid9sWQczzOXBvhyLkBBkYTYDgEdhU+\nLxK02L+lnYPb2mmpf77QFlKQzCWJOwlAYupzbwCWMw1QLrFsjEtjV7g8drlkS9aIEWRjeBUbw6tp\n9tWXvYZnbVifzYGcK/vIHZ8kcew0yTMXkNkisyw18K9fS+i1XfjXr0Gr4lyl/JSBQNd0TN0kbIcJ\nWDbWPL8zCoVCoVh6vnB1ALvMTaZqp7crzO7NDaztjmIYS7dBJLPZgmLkLEOZUfo+/Rtut2iIIt3L\ndTR6Q11sj6yjK9BW0c0vmUjmhcjzfeAVYcHf3oZ+cD/W2jUEbeM5K/pqYXYqQ0fDNCyidlgJkAqF\nQlGARMphdCqJZRmYizDtlc64fHD8Pp+eHUAUyInsbovyh2/1sqZj+SbkCol9UkpcV6ChEQ6ahIM2\nRgnPQ094nBg4x0e3PyOeSxY8vi3czLu932Rr64aKC5FSiHxWZCaLbpeRkfmlaciAmZ9knTp7jkc/\n+WfcWHze830tLaz8/veIbtpYlQKfcB2kkJjhEP7alqrOslS8uqgqVaFQKBTPIYRkMpYhlsxhWXpR\nIeSLzVQ8w2fnH/N532OS6eIzlAJ1cf7w4A72beh4YQNJSEEilyCRS6BpWsGNm1KnAbRIpOh1Pj3/\niZXZxdFL3Ju5X9K5tmayNtTN5sgaOv2tZRW3UkqEl98yNA0dv2Xg91vY83T/SynJ3rlP4ugpMtdv\nUWw0lh4JE9q7g9C+nZh11WlP8mWbs6gdwKcESIVCoahaco7HyGQSt4pcHWZpCjbiM3xkvSxSgphu\nxKgr3kUAZqcha9mzuZHaaPnWYgvB+eQIcnCo4HE/ebOGR20+8oVB4eKgxgyzPbqOLeHeBdvKfxmZ\nyeKeOIV3+iw4hetIrWMlwUOvE9ywBl+V/R4JKfCEh0TD0g0Clp+QHSi6NpmdeNB0A6A4D2GFQqH4\niiClZGw6TSLlLMo+h5SS01eH+cnhO8SS8zfo1kf9fO/QanZtaEGvQmEKZqchJT7boKk2ULLbhJCC\nvqFrfHjrE8ZT8+coArRFmnlvzSG2tK6vuBAJ4KXSuOMTebeDEsXI2WzIoB0gbIee7h9lRkcZ+Id/\nIn7j5rznG8Egbb/7Pk1vvF51lqdSSoTjoBkGdl0dZjhc1Y3iilef5d9lVigUCkXVkEg5jE+nuPuF\nFQAAIABJREFU0XUWLcy9FO49nuHTsw85f3OsYGfhl/FtPA6BNMdT99nNX2GS37gTUhDPxUnkkuha\nvpu8EKVMA8jHg2T+rx/h/5/+quhJycn0JBdHL3Fp/AqpEkLZNTS6Am1siayhN9iFVUY3/LNTkJZl\nEvbb+OwXbVi/jHRdUn1XSPz2JM5Q8RGJ9qouwgf2ENi8vuoKcUe4SMlzAqSaMlAoFIrqx/MEY1Np\nUlkX29IXPT+xHLqjXdQY9Qw+tnGHu5CeRWDX3K4Lz7JqZYidm2vZtLp+Sachv4yUMm9zWkTe4mhD\n4fpKQ2N1cCU7ouvpCayo+KSAdBy8s+dxj5+EdGFrOKu7k+g738S/pqdqphaklLgybxFvagZ+0yYY\nCGE9Yw9f8BpCIF0HdAMzFMQfbUa3bQ7+/CelWXAoFArFK4zrCYbGEwixOHsdg2MJ/v7XN7k9MH+v\nh982+M6Bbt7a3fFchMxiI4t4ds/iOHkXgUjQIhK00ctwB7g1fo9/ufExA7HCTUzNoQa+s/ZNtrVu\nXBQhUkqJOzGNSCZKyooUMm9Pa+n602nI2WevcByGP/qYkV9/jHTnidXRNBoPHqD93/wuZnhhETqV\nRgqBcBx0n42/tQUzUNmGMIViLtQOm0KhUCjy9qyTKXKOh7XMneCeEPTdGuOTMwPce1z+PokeyAfG\nDyWGOPzwCO90f5tELkE8l8DQ9JIC24udBphFDg7hfPIZ9vvvzHmMK1xuTd6mb/QiD2IPi742QL1V\nw5bIGjaFV5ecqfTcFKSuE7AN/D6r6AwkL5kiefIcieOnEbHicqA02yK4axvhA3uwWptLWu9iMitA\nGpqGqVvU+qL4TFsJkAqFQvGK8GxOpGkYVdFM9TLGp9McPjfA4wtbcd0nIpJRYFLPcDAaH7N7Ux3v\nb9pSFQKZuP8AObXwobqA7mNbdB3bI+sWnG/9MqQQeJeu4H72OcQL1yp210qi776Jr0qEyFmHBkPT\nsA2biBXGb/jQS5hWkJ6H8Fy0JyKk9USEVCgUiq8jybTDyOQTi1azsv+fz+RcPjh6n0+KsGc9sKWN\n735zNTXhpcl8nsUVLqPp0XmPkUKS8wS2aZScDfksw/FRfnHjY66N3S54bEOglnd7D7GrfQuGvjg1\nnHQ9nNExEKLo5+BsHnPQ9NMQDL3gQhC/dZuH//XvyY6OzXud0KoeOv74jwh2dpS9/sUgXyN4mMEA\n/lZly6pYetSOm0KhUHyNkVIyFcsyFc9i2/qyipHprMuxi4McPjfAxEzhLnYAtML5PxLJuaELbGnY\njK5rJQmRUNo0wDMn4fVdRH7n7ReK+KnMNH2jF7k0epmUW/w0pK1ZbAj3sCXSS7uvqaSXAykkrhBf\nZEH6ffhso+AU5LO4k1PEf3uC1Ok+ZBF2ZwBGQx3hg3sJ7d6OHvAXfa/FwhMCIQUaYBk2db4otunD\nXKSXH4VCoVAsHqmMw+hUCo3qzYm8PzjDx6cfcuHm6JMyorjnrtV5A6N+mOZwPW9v+E5ViGQAYmwc\nslkk8LjZ4mJvgN85Fiv6/Da7gZ3RDawP9yxK84+UEnHvPu4nR5AFNgkBrJXt1Lz7Jr51q5f1ezyb\nR6WRr1PLzYGUnodwXTTTzG8y1tSoTUaFQvG1RkrJ+HSaeCpXlkVrNufyyxP9c379bz+8xoPBONOJ\n7LzX6WmP8idvr6O7LVryGhZKPBsnloujMXdTi+O4hEMBGmsDmEU2Kr94nwS/vHWYEwPnkQWs2qO+\nMO+s+SavdexY1GZgkUrjjk2gWVZBd6b8NKSHqRlE7TBBO/DCtKabSvH4pz9j4tiJea9lRiKs+N53\nqd+3t2pqOMjnQyIkZk2UQE1N1TlWKb4+VOebm0KhUHwNyWRdfvzJrTm//uNPbvGDt9fhL9G3fy6+\n2MjT8PuWrxCZjmf59OwAv+17RCZbWGAEwMpgtjzEbCpusnA6O81oepQVkRUlr6/caQA5PY3of4DR\n042QgjtTd7kw0ldyNuRKfwtbI72sC3Vjl5Bd6LkCQb673mcb1Ph982ZBzkXu0SDxI8dJX7pWtCjr\n611F+PV9+Nf3opUgelaapxt8mo6lGYSsAAHbvyQZkMLJ5acv87a9pYWEKRQKRZUx2/FfSiPLYjHr\n6pDJeVU5ESmk5PKdcT4+9ZA7j8qbJjSbHtMcbOZPN/wxdomNVIuJkIJbnT7ObQgy2mBh50TBc3RP\n0vswy87GbXRuO7B4axsaxv3kCKL/QcFjzZYmat57C/+mdcuyUfisDaulmQQsHyEriFmCDevTaz0r\nQoZD+CMRJUIqFIolo5rqgy/juIKhiQRSUJYYOZPI8n/80wUejSbnPObirflf86Ihmz94cw17N7Uu\neU6kkIKJ9ASO52AZFp6ce6+lrTFCyFeeXafjORy5f5Lf3P2crDd/bqbf9PGtVQf5Rvdr+MyFT+2L\nTJbpX3w059enfvIBNe+9Oe+ehCPy35eA6XvpNOQs030XGfjHf8KZmacRS9NofP0g7d/9PcxgsLgP\nsQQIJwdomDU12DVRlQ+pWHaUIKlQKBRVwFQ8w//yn09wf3Du4uafD9/hws1R/td/d4DaSPkWH9Wy\nkTc4nuA3px5y6uowXpH5kM1NBlPRcxh1I2h68ROLrnSZTE+VJ0g+mQYomUyW+OgQ1+whLoz0EcvF\niz41pPvZHOlla6SXerumqHOklHhefmPQMA3CQQu/z8Aoo9iUUpK9fZ/44aNk7xQpoJomoV1bCb++\nb9lsWYUUuFLkJww086kAaWqlb/CVdf9nREhfUxNGIICm6xz8+U+KHPlVKBSK6sL1BD/62WU+73sM\naLyxvZ0f/v4WzDKyhBbKrKvDdCKLZelVJ0Y6ruDU1SF+c/ohwxPFOyC8jNfa93JwxcGqESMdz+Hi\n2GVO62eYeb24uiSQFmy/mWbr7TQhT8f6885FWZuMx3E+/Qxx+WrBY426GqLvvElw55Yl34ybbZLS\nNR2fbhHxlW7DOouUEpHLoRkGZiSsREiFQrHkVFN98DJmElkmZjLYlo5WhkVrNucWFCPnQ9Pg0M6V\n/Js3VhPwL/3We9rNMJmexNANzCJqiXJiG6WUXBq5zi+u/5qJ9PwNWKZu8EbXXr69+g1CdmWEOm8m\nxvD/9n+Se/hozmOSR0+Su3ufxh/+BUbki6ib57IhfRH8ln/O7EonFmPgH3/M9IW+edcTWLmSzh/8\nCaGe7nI+zqIgXAfQsOvrMSORqprWVHy9UYKkQqFQLDOZrFtQjJzl/mCM//k/H+c//o9vlDwp+dxG\nnrl8G3l3H03z0ckHXLpT3NCYrmvs3tDCt3Z3MMIt/v768CKvcGFIYLjR5GJvkNvyKGKgeOG0x9/O\ntpp1rAl2YhTxVvCsFattmUSDNpapl92hKoUkfeU68cPHcB4NFnWOHg4RPrCH0P7dGOHS8iwrQT4H\nUmJoBgHTJmiHsMqYMCgHKSXSdV4qQioUCsVXgR/97DIfHu9/+vfZP//l97ct6ToyWYfhybw9a7UJ\nkZmsy2/7HvPJmYfMJOafDJilqS7AN3Z182Hsk5d+fX/7a1UhRqbdDOeHz3Nm+BxpN13Suf/2w0nM\n2RKosQ59RelNYfPhpjN4p88iT56GAlbyeihI5NvfIPzaLjRzabZApJRPpi4klm5WxKVBuA5SSAy/\nH397G6Z/+e3wFQrF15NqqQ++jCfkk+Zrd0H1wkenHpYtRva0R/nBO+vpbI2Uff9ykVISy8ZIOAks\n44sJROEJHMet2H0GY8P89PqvuD3RX/DYXe1b+J1136I+UFux+4tMtqAYOYszNML4j/5fmv7qv8N7\nElFUaBoSnuyfnTvPwD/+GC859++C7rNp+93fofnQN6vGAtVzcmi6kRciw2ElRCqqDiVIKhQKxTLz\nkyN36B8qPn+nfyjGPx+5w5+9u77oc+KpHBPTGTRteTbypJRcvTfBr048KNq+LOg3eWP7Cg7tWkld\nJL/hImYa8Rk+sl5pE4uWblEfqCt53QB6UyP4fEVNSd7s9HH+iY1ZnsJiZMgIsDW4ii0166mzC2dK\nCE/gSYmOhs9XvhXrs0jPI3X+MvHDR3HHJoo6x2xpIvLN/QS3b0FbwuyupxMGaJiGRa0vim8JcyCl\nlIgnG5+Gz4/dVKtESIVCURTVbGv2MoSQTyYfnufzvkH+/fe2Lsnn8IRkfDpFMu2UZbe2mMRTOT49\nO8Bn5x6Ryha3ybe2s5Zv7+lk85pGsm6GDz9f5EWWSTwX5/TQWfpG+siJ4nKjv4z5TAlkbFi/4M0w\nKSWu56FJ0G7eQnx6BBmb331Cs0zC39hP5NBBdH/57iLFMlujGJqObdjU+CLYpj3n1EUxSCEQjoNm\nmdh1dfmNRVVzKBSKZaQa6oOX4bgej0cT6IaGbZX/biil5MKN0ZLP0zT4s3fXc3Bb+5LbswJ4wmM8\nPYGQ3lMx0nU9kBrhkEU0unCBNJlL8ctbhzn28GzBnMjV9V18d/07dNZWtiEJYOaDj8kNvPg7OBfO\n0AgzR46x4nfef2k25AvHx+MM/P0/Mt13cd7johs30PGDP8XXUF/0WhaTWSHS19CAFVl6QVyhKJbq\neqtTKBSKrxlSSo5fHCw2mu/JOXD04mN+8E7h3JtM1mF0Oo3nyQUV5eUihOTcjRF+deIBj8cSRZ3T\nVBvgW3s72b+57QXxtDvaRZ2vluHUSEnriNpR2sPtJZ0zi97ThVZXixwufM9P90bI2cVtEnWFO9jh\n62F1qBPTnL9b3nM9BGAaOgG/ScBnVsQORzouybN9xA8fxZuaKeoc3+puwocO4F+3ZsmmEJ/PWfIT\nsgJYSzg5IoXI5zNpYPj92PV1eRFSdRoqFIoiqHZbs7lIZV3iqRfFqHgqRyrrEg4s7v+H46kc49Np\nDEOrKjFyKpbh16cecPTiII5bRIaiprFrQzNv7+2kszXfeJTfNKy+eOGpzDQnB09xaewyQhb+bIZX\nRAHb3Iy5f29Z6xFC4AmBjo5tGQSnJkh++Gty/QPzn6hphPZsJ/rOmxg1i7ch91yNolcuq3q2+UnT\nNYxgEH9ri7JkVSgUVcNy1wcvXVPGYXgiiW0ZC35Hu/dohslY6YkbtqGzojG0LGJk2s0wkZ7E0k10\nzcBxPExDpzbiJ+jPuwelnNKcDp5FSMGpgQv8683fkCxwnaZQA99d/zabmhcnp1lKSfL0BUraRAPc\nKzcJfe8PC65pdirSTcy9f2WEQnT80fep27O7KvYEvCc27v6mJszQ0rtWKRSlUj1vdgqFQvE15Eb/\nFGPTpReGE9MZbj6YYn33yzuxvpwTudR7np4nOHV1mF+d6Gd0qrjP190W5Z19XWxf2zRnV6WmaWxr\n3sJwf2mC5IbG8othTdMwtm/F/eg3JRe9X8Zv+NnStJntgdXUOSaa/fIgdyklwhNIwDQNwiEfAVsv\nK2foZYicQ/LUOeJHjiMKTBcAoGkEtmwgcugAdkflOxy/jCs8hBQVyVkqF+G6SM9DM02MgB9ftAnD\nt/jTFQqF4qtHtdqaVSuzNUzW8ZalmWouxqbTfHSinxOXh4rKvvZZBge3tfOtPR001ASe/nvaSTOZ\nmUQssKaoJOPpCU48PsnV8WsFJx4AfLrN1n6HbWen5j+wuRnfn//xnPXOy/BcgZACQzcI+AwCfj9a\nOk3sV79m6vT5guYTvnVrqP3dtxctzzqfO5V3arAMm7oK1ihPLVl9Pvwtzar5SaFQKIpgJpFlYjqN\nr8RIm7kYnc7XIKWSdQWjU2lWraycNWkxzGRm8hatukXOFfgtg6a6QMWauR5MP+InVz/k4cz8kS5+\n08d7vYd4o2svxiK6F2Vv38OdKFB/vITc9DTJ+/2EV/W89OtuKsXAP/wTU2fPzXuduj27WfmHf1AV\nE4hPhchmJUQqXi2UIKlQKBTLyOBEgnSRNl/Pksq6DI4nXxAkpZRMJ7JMxbJY1tLnRDqux/FLQ3x0\n8kHRXYVbVjfyzr5O1nTUFtx0kVKyq3UX50cuMpYeK+r6zcFm9rXtK+rYubC+dQjv8lW8wUHut9us\nflxcRtQsraEWdrbsYENNL+bkDNKTaF96QXhqRYaGZRmE/X58dvl5kC9D5HIkj58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ZAAAg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\nzLrvv22M/KFgoiOESIFA8HnGtGw6wjGiMRNVkfB6Pruh9O7Gbn7z/Hbaut1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vPUq/lX7k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98i6SSzrg16gpzftJRFdQuorShCJhJYh/qQjovmMUeVDBsvtUVVEyJGSinpfuddWtc8jRPN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       "text": [
        "<matplotlib.figure.Figure at 0x10f6f48d0>"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now let's fit a logistic regression using Statsmodels that considers the influence of patchsize and eccentricity, where here we will code eccentricity as a categorical variable with 3 levels.\n",
      "\n",
      "Note that for simplicity here, I will just fit to all the data (pooled across observers). This should be analysed as a repeated measures design (the conditions are nested within observers), but this is beyond the scope of this course."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fit = smf.glm('correct ~ patchsize + C(eccent)', \n",
      "              data=nat_ims, \n",
      "              family=sm.families.Binomial(link=sm.families.links.logit)).fit()\n",
      "# note we don't have to specify the logit link above, since it's the default for the binomial distribution.\n",
      "\n",
      "print(fit.summary())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                 Generalized Linear Model Regression Results                  \n",
        "==============================================================================\n",
        "Dep. Variable:                correct   No. Observations:                51050\n",
        "Model:                            GLM   Df Residuals:                    51046\n",
        "Model Family:                Binomial   Df Model:                            3\n",
        "Link Function:                  logit   Scale:                             1.0\n",
        "Method:                          IRLS   Log-Likelihood:                -33392.\n",
        "Date:                Tue, 24 Feb 2015   Deviance:                       66784.\n",
        "Time:                        20:40:48   Pearson chi2:                 5.10e+04\n",
        "No. Iterations:                     7                                         \n",
        "====================================================================================\n",
        "                       coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
        "------------------------------------------------------------------------------------\n",
        "Intercept            1.2857      0.025     51.341      0.000         1.237     1.335\n",
        "C(eccent)[T.4.0]    -0.5116      0.024    -21.134      0.000        -0.559    -0.464\n",
        "C(eccent)[T.8.0]    -1.2084      0.031    -39.076      0.000        -1.269    -1.148\n",
        "patchsize            2.0228      0.036     55.684      0.000         1.952     2.094\n",
        "====================================================================================\n"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "What do the coefficients mean?\n",
      "\n",
      "The intercept is the value of the linear predictor when the target is at 2 degrees from fixation and log patchsize is zero. In this case, the model predicts performance will be `logit(1.2857)`, about 78% correct.\n",
      "\n",
      "The two coefficients for eccent show the offset applied to the linear predictor when the eccentricity is 4 or 8 degrees, relative to an eccentricity of 2. So when log patch size is zero, we predict the performance at 4 degrees to be `logit(1.2857 -0.5116)`, about 68% correct. Similarly, a patch of log size zero presented 8 degrees from fixation would be expected to yield 51% correct. \n",
      "\n",
      "The same sized patch is harder to detect, the further away from fixation it is presented.\n",
      "\n",
      "Finally, the `patchsize` coefficient shows the change in the linear predictor for a one-unit (i.e. 1 log unit change) in the size of the patch. At 2 degrees, a patch of log size 0 yields 78% correct (see above); if the patch was log size 1 it would be expected to yield `logit(1.2857 + 2.0228*1)` or 96% correct, on average."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Conclusion: Binomial models\n",
      "\n",
      "The GLM can be used to model a dichotomous response variable by assuming that variable is distributed according to a binomial distribution. Dichotomous response variables are found often in neuroscience and psychology: whenever we talk about \"percent correct\" or similar variables (like the psychophysical dataset above). \n",
      "\n",
      "To do this, we \"squash\" the linear predictor through the `logit` function, which gives it bounds between 0 and 1.This squashing procedure and binomial family is an example of changing the identity link function and the error model. It's what makes the GLM \"generalised\". \n",
      "\n",
      "Note that nothing changed about how we construct or interpret the design matrix for our model: everything we've learned about design matrices still apply."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Poisson regression\n",
      "\n",
      "It's common in neuroscience to measure the spiking activity of neurons. Spikes over time can be thought of as \"events\", and thus the number of spikes in a time interval as event counts. \n",
      "\n",
      "Counts are discrete and non-negative - thus modeling their distribution requires again a different type of GLM. Luckily, we can again achieve that by changing the link function.\n",
      "\n",
      "As a very brief example, we consider a neuron recorded from V1 while showing a grating with two different orientations at two different contrasts. What type of design do we have here?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "spk = pd.read_csv('../Datasets/neuron2.txt', sep='\\t',index_col=False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "spk.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>spikes</th>\n",
        "      <th>contrast</th>\n",
        "      <th>orientation</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 6</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 6</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "   spikes  contrast  orientation\n",
        "0       3         1            0\n",
        "1       6         1            0\n",
        "2       3         1            0\n",
        "3       3         1            0\n",
        "4       6         1            0"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.factorplot(\"contrast\",\"spikes\",\"orientation\",spk,kind='point')\n",
      "sns.despine(offset=10);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 364,
         "width": 417
        }
       },
       "output_type": "display_data",
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3tjmIkpKSlDqT1BoYhiRJUrv04iev8fspN7KiqjJnTVlJKSfueiT7bDI0xc4ktRaGIUmS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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10dc63ac8>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "What type of effects would you assume when we fit a GLM with appropriate link function?\n",
      "\n",
      "The correct model family for count data is the Poisson family, with the log link function\n",
      "\n",
      "$X\\beta = \\ln(\\mu)$\n",
      "\n",
      "or conversly\n",
      "\n",
      "$\\mu = \\exp(X\\beta)$\n",
      "\n",
      "This takes care of two things\n",
      "* The output of the rhs is nonnegative\n",
      "* The variance of the output increases with the input, as in count data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fit = smf.glm('spikes ~ contrast * orientation', \n",
      "              data=spk, \n",
      "              family=sm.families.Poisson(link=sm.families.links.log)).fit()\n",
      "print(fit.summary())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                 Generalized Linear Model Regression Results                  \n",
        "==============================================================================\n",
        "Dep. Variable:                 spikes   No. Observations:                  156\n",
        "Model:                            GLM   Df Residuals:                      152\n",
        "Model Family:                 Poisson   Df Model:                            3\n",
        "Link Function:                    log   Scale:                             1.0\n",
        "Method:                          IRLS   Log-Likelihood:                -374.91\n",
        "Date:                Tue, 24 Feb 2015   Deviance:                       194.83\n",
        "Time:                        20:40:49   Pearson chi2:                     184.\n",
        "No. Iterations:                     8                                         \n",
        "========================================================================================\n",
        "                           coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
        "----------------------------------------------------------------------------------------\n",
        "Intercept                1.5515      0.083     18.677      0.000         1.389     1.714\n",
        "contrast                -0.0165      0.012     -1.361      0.174        -0.040     0.007\n",
        "orientation             -0.0018      0.001     -1.349      0.177        -0.004     0.001\n",
        "contrast:orientation     0.0019      0.000     11.078      0.000         0.002     0.002\n",
        "========================================================================================\n"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# build a new matrix with expand grid:\n",
      "preds = expand_grid({'contrast': [1, 10], 'orientation': [0, 90]})  \n",
      "preds_2 = preds.copy()\n",
      "\n",
      "preds['spikes'] = fit.predict(preds)\n",
      "\n",
      "\n",
      "# also fit a model with no interaction for comparison:\n",
      "#fit_2 = smf.glm('spikes ~ contrast * orientation', spk).fit()\n",
      "fit_2 = smf.glm('spikes ~ contrast + orientation', data=spk, \n",
      "              family=sm.families.Poisson(link=sm.families.links.log)).fit()\n",
      "preds_2['spikes'] = fit_2.predict(preds_2)\n",
      "\n",
      "# to plot model predictions against data, we should merge them together:\n",
      "# see answer (https://stackoverflow.com/questions/28239359/showing-data-and-model-predictions-in-one-plot-using-seaborn-and-statsmodels)\n",
      "merged = pd.concat(dict(data=spk, \n",
      "                        linear=preds_2,\n",
      "                        interact=preds),\n",
      "                   names=['type']).reset_index()\n",
      "\n",
      "g = sns.factorplot('contrast', 'spikes', 'orientation', \n",
      "                   data=merged, \n",
      "                   col='type',\n",
      "                   kind='point',\n",
      "                   size=3.5)\n",
      "g.fig.subplots_adjust(wspace=0.3)\n",
      "sns.despine(offset=10);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 257,
         "width": 817
        }
       },
       "output_type": "display_data",
       "png": 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leOCtv/PgW3/f4GOUl5azZdc+XDz8PPp165vF7CRJUja8t/hDfjP+epZULcsY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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10dc6fa58>"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Note that this is particularly important if the counts are low, because than their non-negativity plays a role."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(fit_2.summary())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                 Generalized Linear Model Regression Results                  \n",
        "==============================================================================\n",
        "Dep. Variable:                 spikes   No. Observations:                  156\n",
        "Model:                            GLM   Df Residuals:                      153\n",
        "Model Family:                 Poisson   Df Model:                            2\n",
        "Link Function:                    log   Scale:                             1.0\n",
        "Method:                          IRLS   Log-Likelihood:                -437.65\n",
        "Date:                Tue, 24 Feb 2015   Deviance:                       320.31\n",
        "Time:                        20:40:50   Pearson chi2:                     328.\n",
        "No. Iterations:                     8                                         \n",
        "===============================================================================\n",
        "                  coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
        "-------------------------------------------------------------------------------\n",
        "Intercept       0.8332      0.075     11.168      0.000         0.687     0.979\n",
        "contrast        0.0976      0.007     14.083      0.000         0.084     0.111\n",
        "orientation     0.0110      0.001     15.441      0.000         0.010     0.012\n",
        "===============================================================================\n"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Do an expanded prediction for many contrasts, compare to linear model:\n",
      "\n",
      "preds_3 = expand_grid({'contrast': np.linspace(0.01, 20), 'orientation': [0, 90]})  \n",
      "preds_4 = preds_3.copy()\n",
      "\n",
      "preds_3['yhat'] = fit.predict(preds_3)\n",
      "\n",
      "fit_lm = smf.glm('spikes ~ contrast + orientation', data=spk).fit()\n",
      "preds_4['yhat'] = fit_lm.predict(preds_3)\n",
      "\n",
      "# to plot model predictions against data, we should merge them together:\n",
      "# see answer (https://stackoverflow.com/questions/28239359/showing-data-and-model-predictions-in-one-plot-using-seaborn-and-statsmodels)\n",
      "merged = pd.concat(dict(data=spk, \n",
      "                        poisson=preds_3,\n",
      "                        linear=preds_4),\n",
      "                   names=['type']).reset_index()\n",
      "\n",
      "merged.tail()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>type</th>\n",
        "      <th>level_1</th>\n",
        "      <th>contrast</th>\n",
        "      <th>orientation</th>\n",
        "      <th>spikes</th>\n",
        "      <th>yhat</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>351</th>\n",
        "      <td> poisson</td>\n",
        "      <td> 95</td>\n",
        "      <td> 18.368163</td>\n",
        "      <td> 90</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 65.976032</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>352</th>\n",
        "      <td> poisson</td>\n",
        "      <td> 96</td>\n",
        "      <td> 18.776122</td>\n",
        "      <td> 90</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 70.202318</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>353</th>\n",
        "      <td> poisson</td>\n",
        "      <td> 97</td>\n",
        "      <td> 19.184082</td>\n",
        "      <td> 90</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 74.699331</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>354</th>\n",
        "      <td> poisson</td>\n",
        "      <td> 98</td>\n",
        "      <td> 19.592041</td>\n",
        "      <td> 90</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 79.484413</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>355</th>\n",
        "      <td> poisson</td>\n",
        "      <td> 99</td>\n",
        "      <td> 20.000000</td>\n",
        "      <td> 90</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 84.576017</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "        type  level_1   contrast  orientation  spikes       yhat\n",
        "351  poisson       95  18.368163           90     NaN  65.976032\n",
        "352  poisson       96  18.776122           90     NaN  70.202318\n",
        "353  poisson       97  19.184082           90     NaN  74.699331\n",
        "354  poisson       98  19.592041           90     NaN  79.484413\n",
        "355  poisson       99  20.000000           90     NaN  84.576017"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "g = sns.FacetGrid(merged,\n",
      "                  hue='type',\n",
      "                  col='orientation')\n",
      "g.map(plt.scatter, 'contrast', 'spikes')\n",
      "g.map(plt.plot, 'contrast', 'yhat')\n",
      "g.fig.subplots_adjust(wspace=0.3)\n",
      "sns.despine(offset=10)\n",
      "g.add_legend();\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 221,
         "width": 502
        }
       },
       "output_type": "display_data",
       "png": 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zDQ8/lIFDnYEj9RUNn7Rn5lzgPmBMRIytvRYRg4AdgVeA/wC3U/xO9ulQbyiw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\ni8Wk1bu3tyyQL1Ds66XY20exMGRfX4Fib2+yP31ZUOjtZVd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+M8a4CXg4PV6Nqr1s/hp4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\nRK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x105e302e8>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can see that the linear and the poisson models give very different predictions outside the range of this data. Furthermore, the linear model \n",
      "\n",
      "- can predict negative rates\n",
      "- assumes that variance homogenous, but for rate distributions (i.e. Poisson) the variance scales with the mean."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Conclusion\n",
      "\n",
      "The GLM allows us to specify different distributions for the response variable $y$ and for the link function $f()$. In this notebook we've considered two examples from the context of behavioural / neural science: percent correct data (binomial regression) and spiking data (poisson regression). The following table (adapted from John Kruschke's book, [*Doing Bayesian Data Analysis*](https://sites.google.com/site/doingbayesiandataanalysis/)) shows, for many types of response data, the appropriate error model and the most common link functions. \n",
      "\n",
      "\n",
      "Scale type of $y$ | Typical noise distribution of $y$ | Typical link function \n",
      "------------------| --------------------------------- | ---------------------\n",
      "metric (continuous) | normal | identity\n",
      "dichotomous (0 or 1) | bernoulli | logistic\n",
      "nominal (unordered categories) | categorical | softmax\n",
      "ordinal (ordered categories) | categorical | thresholded logistic\n",
      "count | poisson | log\n",
      "\n",
      "In this course, we've looked extensively at the first row, and touched on dichotomous and count data here. The GLM offers a powerful framework for modelling a wide variety of data.\n",
      "\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.core.display import HTML\n",
      "\n",
      "\n",
      "def css_styling():\n",
      "    styles = open(\"../custom_style.css\", \"r\").read()\n",
      "    return HTML(styles)\n",
      "css_styling()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<style>\n",
        "    @font-face {\n",
        "        font-family: \"Computer Modern\";\n",
        "        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunss.otf');\n",
        "    }\n",
        "    @font-face {\n",
        "        font-family: \"Computer Modern\";\n",
        "        font-weight: bold;\n",
        "        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunsx.otf');\n",
        "    }\n",
        "    @font-face {\n",
        "        font-family: \"Computer Modern\";\n",
        "        font-style: oblique;\n",
        "        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunsi.otf');\n",
        "    }\n",
        "    @font-face {\n",
        "        font-family: \"Computer Modern\";\n",
        "        font-weight: bold;\n",
        "        font-style: oblique;\n",
        "        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunso.otf');\n",
        "    }\n",
        "    div.cell{\n",
        "        width:850px;\n",
        "        font-size: 11pt;\n",
        "        margin-left:16% !important;\n",
        "        margin-right:auto;\n",
        "    }\n",
        "    h1 {\n",
        "        font-family: Minion Pro, serif;\n",
        "    }\n",
        "    h2 {\n",
        "        font-family: Minion Pro, serif;\n",
        "    }\n",
        "    h3 {\n",
        "        font-family: Minion Pro, serif;\n",
        "    }\n",
        "    h4{\n",
        "        margin-top:12px;\n",
        "        margin-bottom: 3px;\n",
        "       }\n",
        "    div.text_cell_render{\n",
        "        font-family: Optima, sans-serif;\n",
        "        line-height: 145%;\n",
        "        font-size: 12pt;\n",
        "        width:850px;\n",
        "        margin-left:auto;\n",
        "        margin-right:auto;\n",
        "    }\n",
        "    .CodeMirror{\n",
        "            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
        "    }\n",
        "    .prompt{\n",
        "        display: None;\n",
        "    }\n",
        "    .text_cell_render h5 {\n",
        "        font-weight: 300;\n",
        "        font-size: 12pt;\n",
        "        color: #4057A1;\n",
        "        font-style: italic;\n",
        "        margin-bottom: .5em;\n",
        "        margin-top: 0.5em;\n",
        "        display: block;\n",
        "    }\n",
        "\n",
        "    .warning{\n",
        "        color: rgb( 240, 20, 20 )\n",
        "        }\n",
        "</style>\n",
        "<script>\n",
        "    MathJax.Hub.Config({\n",
        "                        TeX: {\n",
        "                           extensions: [\"AMSmath.js\"]\n",
        "                           },\n",
        "                tex2jax: {\n",
        "                    inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
        "                    displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ]\n",
        "                },\n",
        "                displayAlign: 'center', // Change this to 'center' to center equations.\n",
        "                \"HTML-CSS\": {\n",
        "                    styles: {'.MathJax_Display': {\"margin\": 4}}\n",
        "                }\n",
        "        });\n",
        "</script>"
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